Utilization and Costs of Antipsychotic Agents: A Canadian Population-Based Study, 1996–2006
Bibliographic record
Abstract
OBJECTIVE: This study evaluated the prescribing patterns and costs for antipsychotic agents in the population of the Canadian province of Manitoba over the past decade. METHODS: A population-based study of antipsychotic utilization and costs was conducted on data collected from the administrative databases of the Manitoba Population Health Data Repository and the Statistics Canada census between index years 1996 and 2006 (April 1, 1995, through March 31, 2006). RESULTS: The total annual number of antipsychotic prescriptions dispensed in Manitoba increased by 227% between 1996 and 2006, and the prevalence of antipsychotic users increased by 62% over the same time interval. The fastest-growing segment of antipsychotic users in Manitoba appears to be young males, who increased from .16% in 1996 to .88% in 2006. The highest numbers of prescriptions were reported for schizophrenia, dementia, and conduct disorder. Annual expenditures for antipsychotics increased from $1.7 million in 1996 to $22.0 million in 2006 (expenditures are in Canadian dollars). The cost of second-generation agents reached 80% of total antipsychotic expenditures in 2006; risperidone was the most prescribed agent in all age groups of patients. The per-patient annual cost of antipsychotic pharmacotherapy increased by approximately 680% between 1996 and 2006 in Manitoba. CONCLUSIONS: The number of antipsychotic prescriptions and the prevalence of users of antipsychotic medications increased significantly in Manitoba over the study period, despite a steady-state population of approximately 1.2 million. Incremental costs relative to the use of antipsychotic medications can be explained by the market penetration of the second-generation agents and their expanded use in the treatment of various diagnoses.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".